CHESDA: continuous hybrid and energy-efficient secure data aggregation for WSN

Data aggregation is an effective mechanism to prolong lifetime in the wireless sensor networks by preventing extra data transmission. However, it may have some adverse effects on accuracy, confidentiality, delay, and privacy preserving. Sensing nodes tends to trade-off between energy demand and security issue. Data can be filtered by temporal correlation of sensory data, and thus, network traffic is controlled. Furthermore, data transmission via unnecessary nodes can be controlled by spatial correlation of sensing devices. This, in turn, prolongs network lifetime. CBDA algorithm was proposed by Hu et al. as a technique based on tree and chain formation and slice-mixing. However, we showed the proposed scheme was vulnerable to stolen key set attack and failed to provide forward secrecy. This has been fixed in proposed key distribution and agreement scheme. In this paper, we propose a continuous hybrid and energy-efficient secure data aggregation (CHESDA) algorithm that trades off between privacy preserving, data integrity, communication overload, delay and accuracy and then chooses the best scenario based on application and importance of the parameters. Here, privacy preserving is maintained by slice-mixing technique. Fuzzy logic is applied to choose optimal slicing in each subtree, and GNY logic is utilized to verify key authentication scheme. Results of analysis and simulations indicate that CHESDA, compared to PECDA and SMART, is more energy-efficient and highly secure with lower communication overhead.